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This study examines factors affecting the adoption of Generative AI (GenAI) tools in higher education through the Technology Acceptance Model (TAM). A Meta-Analytic Structural Equation Modeling (MASEM) was utilized to analyze studies centered on TAM variables—Perceived Usefulness, Perceived Ease of Use, Attitude, and Continuance Intention—selected via the PRISMA protocol from databases like IEEE, Scopus, and Emerald, with analysis conducted using IBM SPSS. Findings confirm that Perceived Ease of Use strongly impacts Perceived Usefulness and Attitude, while Perceived Usefulness significantly influences Continuance Intention and Attitude. These results validate TAM’s relevance in explaining GenAI adoption and highlight growing acceptance due to enhanced learning and administrative efficiency. Institutions must create policies for responsible AI use, promoting academic integrity and skill development in higher education for effective integration.

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The Technology Acceptance Model (TAM): A Meta-Analytic Structural Equation Modeling (MASEM) Approach to Explaining the Adoption of GenAI Tools in Higher Education

  • 会议论文

  • 发表日期：

    2025年

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  • Agostinho Sousa Pinto,
  • António Abreu,
  • João Vidal Carvalho,
  • Milena Carvalho,
  • Susana Martins,
  • Jerónimo Paiva

摘要

This study examines factors affecting the adoption of Generative AI (GenAI) tools in higher education through the Technology Acceptance Model (TAM). A Meta-Analytic Structural Equation Modeling (MASEM) was utilized to analyze studies centered on TAM variables—Perceived Usefulness, Perceived Ease of Use, Attitude, and Continuance Intention—selected via the PRISMA protocol from databases like IEEE, Scopus, and Emerald, with analysis conducted using IBM SPSS. Findings confirm that Perceived Ease of Use strongly impacts Perceived Usefulness and Attitude, while Perceived Usefulness significantly influences Continuance Intention and Attitude. These results validate TAM’s relevance in explaining GenAI adoption and highlight growing acceptance due to enhanced learning and administrative efficiency. Institutions must create policies for responsible AI use, promoting academic integrity and skill development in higher education for effective integration.